Field of the Invention
The invention relates to a method for controlling process events of a technical plant.
The method is suitable for the optimization and analysis of process events of a power station or a power plant.
It is generally known to detect individual process variables by measurement, to consider them and also to evaluate them as a function of the process state. In addition, it is known to model and to predict individual process variables by applying mathematical, statistical or neural algorithms. One disadvantage of these signal-supported methods is that in regions in which a large number of process signals are observed, the interpretability and comprehensibility--and therefore the current knowledge about the process state--is lost. When hundreds of process variables change simultaneously during transient process events, no estimate of the current process state can be obtained, and in particular it is impossible to assess the course of the transient process event.
With conventional methods, when non-linear relationships exist between the process variables, it is not possible to make any determination as to which process variables have to be changed simultaneously or what percentage change is suitable, in order to transfer from a current process state into a desired process state. A well-known technique for solving this problem is to carry out a what-if simulation for previously firmly defined steady-state operating regions, during which the influence of each individual process variable on the desired target variable is ascertained. One or more input signals can be changed, and the resulting behavior of the target variable can be calculated. A disadvantage of this method is that lengthy trial and error is required to obtain information as to which process variables have to be set and to which value a particular process variable must be set in order to move the process in a required or desired direction.
The transient process regions present a major problem because there is a lack of information about what can actually be viewed as a desired event in these regions. A combination of, for example, 200 measurement signals cannot readily be viewed to see whether it represents an optimum or a faulty process state.